The flow of network traffic on business and academic networks has been on the increase. This necessitates the issue of proper management of traffic network flow in order to ensure optimum performance. Network analysis looks at certain performance measures with a view to gaining insight into the pattern of flow in the network. This research employs a queuing model and regression technique to analyse the performance of the Federal University of Technology, Akure (FUTA) network. Traffic data flows were captured over a period of four weeks using Wireshark capturing tool at different strategic locations in the campus. The arrival rate and service rate were used to obtain the intensity of traffic at these locations. Analysis of the data assisted in determining the variability in the traffic flow. The major contribution of this research is that it developed an empirical model that identified variables that significantly determines network traffic. The model could assist network administrators to monitor, plan and improve on the quality of service.
This paper’s primary contribution is that it employed multiple regression to identify the factors that determine network traffic. The model could be used to plan the usage and monitoring of computer networks